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Published in:
23-08-2022 | Curmudgeon Corner
The rise of machine learning in the academic social sciences
Published in: AI & SOCIETY | Issue 2/2024
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Excerpt
‘In considering any new subject, there is frequently a tendency, first, to overrate what we find to be already interesting or remarkable; and, secondly, by a sort of natural reaction, to undervalue the true state of the case’– Ada Lovelace, 1842
Fig. 1
The Rise of Machine Learning in the Academic Social Sciences. The blue line indicates the rolling one-year frequency at which a range of ML based terms are observed in abstracts for the
SOCI (social sciences), BUSI (business) and ECON (economics) Scopus subject areas, with orange annotations indicating each individual long-run average for the previous year at that point in time. The inset scatter plot indicates the frequency of use of various clusterings of terms compared to a selection of other subject areas indexed by Scopus, where ‘Basic ML’ indicates a simple mention of ‘machine learning’ or ‘artificial intelligence’. The x-axis of the inset relates to subject areas. For example, ‘Trees’ pertains to a variety of tree-based methods. Further information is available at github.com/crahal/ML_in_SocSci and via a DOI on Zenodo: 10.5281/zenodo.5918226
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